"""
Created on Fri Mar 11 05:36:13 2011
@author: musselle
"""
import scipy.io as sio
from utils import analysis
from PedrosFrahst import frahst_pedro
from Frahst_v3 import FRAHST_V3
from artSigs import genCosSignals_no_rand , genCosSignals
#AbileneMat = sio.loadmat('C:\DataSets\Abilene\Abilene.mat')
#data = AbileneMat['F']
data = genCosSignals_no_rand()
data = genCosSignals(0,-3.0)
e_high = 0.98
e_low = 0.96
alpha = 0.96
holdTime = 0
# My version
res_me = FRAHST_V3(data, alpha=0.96, e_low=0.96, e_high=0.98, sci = -1, \
holdOffTime = holdTime, r = 1, evalMetrics = 'T')
#metric_me_5, sets_me, anom_det_tab_me = analysis(res_me, AbileneMat['F_g_truth_tab'])
# Pedros Version
figure()
plot(f_qq)
title('Deviation from orthonormality')
figure()
plot(e_qq)
title('Deviation of true tracked subspace')
return e_qq, f_qq, g_qq
if __name__ == '__main__' :
streams = genSimSignalsA(0, -3.0)
# streams = array([[0,0,0], [1,2,2], [1,3,4], [3,6,6], [5,6,10], [6,8,11]])
streams = genCosSignals_no_rand()
streams2 = genCosSignals(0, -3.0)
energyThresh = [0.96, 0.98]
alpha = 0.96
# rr = 4
sci = -1
Q_t, S_t, RSRE, rr, E_t, E_dash_t, z_dash, hidden_var \
= frhh_A(streams, energyThresh, alpha, sci)
e_qq, f_qq, g_qq = plotEqqFqqA(streams, Q_t, alpha, p = 1)
figure(); plot(RSRE)
figure(); plot(rr)
plot(f_qq)
title('Deviation from orthonormality')
figure()
plot(e_qq)
title('Deviation of true tracked subspace')
return e_qq, f_qq, g_qq
if __name__ == '__main__':
streams = genSimSignalsA(0, -3.0)
# streams = array([[0,0,0], [1,2,2], [1,3,4], [3,6,6], [5,6,10], [6,8,11]])
streams = genCosSignals_no_rand()
streams2 = genCosSignals(0, -3.0)
energyThresh = [0.96, 0.98]
alpha = 0.96
# rr = 4
sci = -1
Q_t, S_t, RSRE, rr, E_t, E_dash_t, z_dash, hidden_var \
= frhh_A(streams, energyThresh, alpha, sci)
e_qq, f_qq, g_qq = plotEqqFqqA(streams, Q_t, alpha, p=1)
figure()
plot(RSRE)
"""
Created on Fri Mar 11 05:36:13 2011
@author: musselle
"""
import scipy.io as sio
from utils import analysis
from PedrosFrahst import frahst_pedro
from Frahst_v3 import FRAHST_V3
from artSigs import genCosSignals_no_rand, genCosSignals
#AbileneMat = sio.loadmat('C:\DataSets\Abilene\Abilene.mat')
#data = AbileneMat['F']
data = genCosSignals_no_rand()
data = genCosSignals(0, -3.0)
e_high = 0.98
e_low = 0.96
alpha = 0.96
holdTime = 0
# My version
res_me = FRAHST_V3(data, alpha=0.96, e_low=0.96, e_high=0.98, sci = -1, \
holdOffTime = holdTime, r = 1, evalMetrics = 'T')
#metric_me_5, sets_me, anom_det_tab_me = analysis(res_me, AbileneMat['F_g_truth_tab'])
# Pedros Version
res_ped = frahst_pedro(data, r=1, alpha=0.96, energy_low=0.96, energy_high=0.98, \
